Wind turbine pitch optimization

Benjamin Biegel, Morten Juelsgaard, Jakob Stoustrup, Matt Kraning, Stephen P. Boyd

Publikation: Bidrag til tidsskriftKonferenceartikel i tidsskriftForskningpeer review

19 Citationer (Scopus)

Resumé

We consider a static wind model for a three-bladed, horizontal-axis, pitch-controlled wind turbine. When placed in a wind field, the turbine experiences several mechanical loads, which generate power but also create structural fatigue. We address the problem of finding blade pitch profiles for maximizing power production while simultaneously minimizing fatigue loads. In this paper, we show how this problem can be approximately solved using convex optimization. When there is full knowledge of the wind field, numerical simulations show that force and torque RMS variation can be reduced by over 96% compared to any constant pitch profile while sacrificing at most 7% of the maximum attainable output power. Using iterative learning, we show that very similar performance can be achieved by using only load measurements, with no knowledge of the wind field or wind turbine model.
OriginalsprogEngelsk
TidsskriftI E E E International Conference on Control Applications. Proceedings
ISSN1085-1992
DOI
StatusUdgivet - 2011
BegivenhedIEEE Multi-Conference on Systems & Control - Denver, Colorado, USA
Varighed: 28 sep. 201130 sep. 2011

Konference

KonferenceIEEE Multi-Conference on Systems & Control
LandUSA
ByDenver, Colorado
Periode28/09/201130/09/2011

Fingerprint

Wind turbines
Fatigue of materials
Convex optimization
Turbines
Torque
Computer simulation

Citer dette

Biegel, Benjamin ; Juelsgaard, Morten ; Stoustrup, Jakob ; Kraning, Matt ; Boyd, Stephen P. / Wind turbine pitch optimization. I: I E E E International Conference on Control Applications. Proceedings. 2011.
@inproceedings{4767fd84b4744c24ab82f32c6dece0a5,
title = "Wind turbine pitch optimization",
abstract = "We consider a static wind model for a three-bladed, horizontal-axis, pitch-controlled wind turbine. When placed in a wind field, the turbine experiences several mechanical loads, which generate power but also create structural fatigue. We address the problem of finding blade pitch profiles for maximizing power production while simultaneously minimizing fatigue loads. In this paper, we show how this problem can be approximately solved using convex optimization. When there is full knowledge of the wind field, numerical simulations show that force and torque RMS variation can be reduced by over 96{\%} compared to any constant pitch profile while sacrificing at most 7{\%} of the maximum attainable output power. Using iterative learning, we show that very similar performance can be achieved by using only load measurements, with no knowledge of the wind field or wind turbine model.",
author = "Benjamin Biegel and Morten Juelsgaard and Jakob Stoustrup and Matt Kraning and Boyd, {Stephen P.}",
year = "2011",
doi = "10.1109/CCA.2011.6044383",
language = "English",
journal = "I E E E International Conference on Control Applications. Proceedings",
issn = "1085-1992",
publisher = "IEEE",

}

Wind turbine pitch optimization. / Biegel, Benjamin; Juelsgaard, Morten; Stoustrup, Jakob; Kraning, Matt; Boyd, Stephen P.

I: I E E E International Conference on Control Applications. Proceedings, 2011.

Publikation: Bidrag til tidsskriftKonferenceartikel i tidsskriftForskningpeer review

TY - GEN

T1 - Wind turbine pitch optimization

AU - Biegel, Benjamin

AU - Juelsgaard, Morten

AU - Stoustrup, Jakob

AU - Kraning, Matt

AU - Boyd, Stephen P.

PY - 2011

Y1 - 2011

N2 - We consider a static wind model for a three-bladed, horizontal-axis, pitch-controlled wind turbine. When placed in a wind field, the turbine experiences several mechanical loads, which generate power but also create structural fatigue. We address the problem of finding blade pitch profiles for maximizing power production while simultaneously minimizing fatigue loads. In this paper, we show how this problem can be approximately solved using convex optimization. When there is full knowledge of the wind field, numerical simulations show that force and torque RMS variation can be reduced by over 96% compared to any constant pitch profile while sacrificing at most 7% of the maximum attainable output power. Using iterative learning, we show that very similar performance can be achieved by using only load measurements, with no knowledge of the wind field or wind turbine model.

AB - We consider a static wind model for a three-bladed, horizontal-axis, pitch-controlled wind turbine. When placed in a wind field, the turbine experiences several mechanical loads, which generate power but also create structural fatigue. We address the problem of finding blade pitch profiles for maximizing power production while simultaneously minimizing fatigue loads. In this paper, we show how this problem can be approximately solved using convex optimization. When there is full knowledge of the wind field, numerical simulations show that force and torque RMS variation can be reduced by over 96% compared to any constant pitch profile while sacrificing at most 7% of the maximum attainable output power. Using iterative learning, we show that very similar performance can be achieved by using only load measurements, with no knowledge of the wind field or wind turbine model.

U2 - 10.1109/CCA.2011.6044383

DO - 10.1109/CCA.2011.6044383

M3 - Conference article in Journal

JO - I E E E International Conference on Control Applications. Proceedings

JF - I E E E International Conference on Control Applications. Proceedings

SN - 1085-1992

ER -